This invention relates generally to a process for detecting and locating a target in a series of images generated by an imaging sensor. More particularly, this invention relates to a novel process for the automatic detection and identification of targets through the use of computer image processing of data collected by an imaging sensor. This invention also relates to a novel process for obtaining parameter estimates by use of a model with the parameter estimates being used in the automatic target detection process. This invention is particularly useful in the detection of underwater targets from an airborne platform.
Various imaging sensors are used to search areas (or volumes) for particular types of targets which may pose a threat. Examples of such targets include mines and submarines in the ocean, fixed-wing and rotary-wing aircraft, cruise missiles, and rockets in the air, and buried land mines under the soil. Such imaging sensors provide target images in two dimensions. Images in two dimensions can be made either using passive radiation or using active illumination at wavelengths ranging from microwaves, millimeter waves, infrared, and invisible to ultraviolet. These two dimensional images display signal intensity and its variation in two spatial dimensions. Gated cameras used to detect signal returns for pulsed sources (imaging radars or visible lidars) can resolve range from the sensor and therefore can spatially sample a volume in three dimensions. Potential targets within this search volume produce characteristic signatures in the series of images. Examples of imaging sensors exhibiting such target images include, for example, the imaging lidar systems described in U.S. Pat. No. 4,862,257 and U.S. application Ser. No. 420,247 filed Oct. 12, 1989 (now U.S. Pat. No. 5,013,917). Both of which are assigned to the assignee hereof and incorporated herein by reference.
Imaging sensors of the general type described hereinabove typically have a display screen for viewing the detected images (e.g., targets). While a human operator viewing a display screen may provide a highly sensitive and reliable means of detecting targets, in some cases computer image processing will be superior. This is because the computer does not suffer from fatigue and inattentiveness as will be the case for human operators, especially in the environment of an aircraft such as helicopter where noise, heat and vibration can distract from constant surveillance of the sensor display screen. Also, with multiple camera sensors, the visual data rate may be too high for a human to absorb and process effectively. Finally, the inherent complexity of spatial correlations and target signature correlations between images made at different times will require computer processing. For example, the use of a laser sensor to produce data for detection, classification and localization of underwater objects typically produces a large volume of physical measurements which must be scanned manually or automatically to determine the presence of a target. Not only is a large volume of data (approximately 10.sup.7 bits) produced during each scan or glimpse of the laser, but due to the desire to collect such data from a moving platform over large ocean areas, such volumes are produced at high frequence (about every 50 milliseconds). Such a data flow cannot typically be handled by a human being, even augmented with decision aids, but rather requires computer based automatic target recognition algorithms. Hence, there is a perceived need for computerized data processing techniques which will automatically (i.e., without human operator assistance) detect and locate preselected targets, particularly targets submerged underwater.